This page requires that JavaScript be enabled in your browser.
Learn how »
Discovering Wolfram Food through AI
Isabel Skidmore, Gay Wilson and Tommy Peters
Learn how LLMs and AI can enhance Wolfram's built-in food data. See examples of how to use Chat Notebooks and the Wolfram ChatGPT plugin to retrieve nutrition data and analyze it. Learn how LLMs can transform recipe text into structured datasets in Wolfram Language from which we generate graphs. Also see new Wolfram Function Repository food functions that can be easily used by chatbots to complete tasks.
Thanks for your feedback.
Channels: Technology Conference
1311 videos match your search.
|
Eric Mjolsness Collaborative projects have resulted in several Mathematica-implemented modeling languages aimed at general-purpose biological modeling, which is a useful and topical but an indefinitely expandable goal. We update previous work on ... |
|
Jae Bum Jung/Yan Zhuang |
|
Phillip Todd |
|
Василий Сороко |
|
Phil Ramsden |
|
Lou D'Andria Constructing interfaces with Dynamic, DynamicModule and Manipulate is nothing new, but those aren't the only Dynamic primitives available in Mathematica. In this talk, we'll identify and demonstrate some of the ... |
|
Галина Михалкина, Григорий Фридман |
|
Галина Михалкина |
|
Андрей Кротких |
|
Антон Екименко, Кирилл Белов |
|
Физический институт имени П.Н. Лебедева |
|
Григорий Фридман, Олег Иванов |
|
Галина Михалкина |
|
Олег Кофнов |
|
Николай Сосновский |
|
Микаэл Эгибян |
|
Микаэл Эгибян |
|
Леонид Шифрин |
|
Вахагн Геворгян |
|
Алексей Семенов |